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All models are wrong, some models are useful.

  • May 8, 2014 · 7:00 PM

Hello Everyone! We apologize for moving this again but we have found a location that will host us. We look forward to seeing you there! 

 The promise of big data is better predictions. There is no best model that works for all of your data. Model predictive performance is domain specific. What works in one data domain has sometimes very little consequence in another one. Data science needs to get closer to the business and unlock value.

Ensembles are here to stay! Users want a buffet of algorithms that try to "lock-pick" the data for it's secrets. Time is eventually the key limiter. Data science efforts have to make best out of the budget for experimentation and use some kind of co-evolutionary technique that picks the "Champion" model of models for your data. Robust automation and fast analytics can speedup large parts of data smithy. In this talk we discuss ensemble techniques of boosting & trees that when applied on use cases lead to a substantial better predictions. H2O Open Source Machine Learning Platform will be used as a demo bed for GBM and RF.

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  • Henry H.

    Is the talk gonna be posted online?

    1 · May 9, 2014

  • Sze Ki P.

    ????!!! ????

    May 8, 2014

    • Alexander S.

      There's security at the desk that opened the door for me.

      May 8, 2014

    • Sze Ki P.

      thanks. I was in and left

      May 8, 2014

  • Sze Ki P.

    looks like main entrance is locked

    May 8, 2014

  • Twain

    What time will this finish at, thanks?

    May 8, 2014

  • surbhi j.

    May 4, 2014

  • joschka-joseph a.

    What inspired this talk? Was it the "Model Thinking" course on Coursera?

    April 9, 2014

  • Frank C.

    What else besides GBM and RF. Two do not constitute a "buffet"

    April 9, 2014

  • Tina R.

    Topic sounds great

    April 6, 2014

  • Pinar D.

    The location says N/A. Is this meetup still on?

    3 · March 30, 2014

  • Sam Z.

    conflict w/#womenwhocode event the same night.

    March 27, 2014

  • John R.

    Cool topic , looking forward

    March 25, 2014

  • John R.

    Cool topic , looking forward

    March 25, 2014

  • John D.

    Seeking data sci/analyst for wine analytics startup

    March 13, 2014

    • John D.

      Hi Jody,

      March 21, 2014

    • John D.

      Yes, it's a bit of using AI to better decipher/rank wine taste preferences but also incorporating the price of wine.

      Wine Analytix plans to crowdsource wine reviews just as RottenTomatoes does with movie reviews. This aggregated rating is scored and then correlated with the cost of the wine to uncover the true value of a bottle of wine. If interested in such a disruptive wine venture, please contact me at [masked] or[masked]

      March 21, 2014

  • Kristina

    Interested in leaning about big data

    March 12, 2014

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